We propose that noise trading flows impact cross-sectional asset prices through systematic risk factors. In our model, asset-level flows, when aggregated at the factor level, drive fluctuations in factor prices and risk premiums. These factor- level price impacts in turn drive cross-sectional asset prices according to the asset’s risk exposure. Empirically, our model explains the price impacts and cross impacts of underlying assets with a few risk factors. Moreover, the model-implied trading strategy, designed to optimally exploit the reversion in price impacts, delivers strong and robust investment outcomes
Notre Dame, Johns Hopkins Carey, RUC-VUW Joint Virtual Research Workshop, 6th Annual Wolfe Global Quantitative and Macro Investment Conference, Federal Reserve Board, Campbell & Company, MFA Annual Meeting 2023, Southern Methodist University, FMCG 2023, SoFiE 2023 Conference, CICF 2023, Chinese University of Hong Kong, City University of Hong Kong, 10th SAFE Asset Pricing Workshop, UT Dallas 2023 Fall Finance Conference
Financial Markets and Corporate Governance Conference Runner-up for Best Paper